Wise Generosity in Hard Times: Poverty and Mental Bandwidth

By Richard Sebaggala  (PhD)

 In the last weeks of December, I have deliberately chosen to pause my usual writing on the economics of AI and focus on a more fundamental issue: one that shapes everyday economic life for millions of African families. December is a season of celebration, reflection, generosity, travel, and social obligation. Yet, it is also the prelude to one of the most financially stressful periods of the year.

From December into January and February, households transition abruptly from festivity to financial strain. Savings are stretched by food, ceremonies, transport, gifts, and the unspoken obligations that come with being part of a family, community, and church. Almost immediately, schools reopen. Fees, uniforms, transport, and learning materials arrive when financial buffers are weakest. What may seem like poor planning is often a timing problem: heavy spending followed by unavoidable obligations stacked too closely together.

 

This coming cycle is likely to be even more demanding in Uganda. National general elections fall within this same period, adding further strain to the economy. Election seasons divert public spending, slow private investment, heighten uncertainty, and introduce psychological stress. Highly contested elections bring economic costs that extend beyond budgets and markets, reaching into households already under pressure.

 

While reflecting on this convergence (festivities, school fees, elections, and uncertainty), I was reminded of an Oxford-linked study among Indian farmers that explained something many Africans feel but rarely name: poverty and financial pressure quietly reduce our ability to think clearly.

 

The study followed the same farmers before harvest, when money was scarce, and after harvest, when income had arrived. The findings were striking. The same individuals performed significantly worse on cognitive tests when they were financially stressed. The gap was equivalent to losing up to thirteen IQ points. Their intelligence had not changed. What had changed was the mental burden of financial worry.

 

The conclusion was simple but profound: poverty does not only drain income, but it also drains mental bandwidth.

Once this insight is understood, African economic life appears in a different light. Across our societies, financial stress is rarely private. African life is structured around openness (to family, kinship networks, community, and church). Even small signs of stability attract moral expectations to support others. These expectations are rooted in solidarity and shared survival, and they have sustained communities for generations.

Yet, they also carry a hidden cost.

Demands placed on individuals often exceed their income and capacity. Support given rarely satisfies expectations, not because people are ungrateful, but because need itself is deep and widespread. The result is a quiet but persistent form of cognitive taxation. When one individual becomes responsible for many problems they cannot realistically solve, and the mind is left permanently managing emergencies.

Individually, it is very difficult to resist these pressures. Saying no feels unchristian. Setting limits appears selfish. Yet constant exposure to open-ended demands leaves little mental space for planning, growth, or peace.

This is where organised social groups matter in a way that is often misunderstood.  Groups such as Munno Daala are effective not only because they pool resources, but because they create structure. Membership defines contributions, expectations, and beneficiaries. It gives individuals a socially legitimate basis to say, "I am already committed elsewhere." In highly communal societies, this matters enormously.

Such groups reduce the cognitive burden imposed by limitless demands. They allow individuals to focus support within a small, defined circle where reciprocity is clearer, and assistance is assured in times of crisis. This does not mean abandoning family or community. It means preventing one household from being overwhelmed by unbounded expectations.

At this point, it is important to be clear: this argument is not against generosity. In fact, it is deeply aligned with the Christian understanding of giving.

Scripture teaches generosity that is intentional, structured, and sustainable. In Deuteronomy 24:17–22, God commands the Israelites not to harvest everything, but to leave what is missed for the foreigner, the fatherless, and the widow. This was not reckless giving; it was a carefully designed system. The harvest itself was secured, boundaries were clear, beneficiaries were specified, and dignity was preserved through work rather than dependence.

Biblical hospitality was never about limitless personal obligation. It was about creating social arrangements that protected both the vulnerable and the giver. The goal was not to exhaust households, but to reflect God’s generosity in ways that sustained the community over time.

Seen this way, organised groups like Munno Daala are not unchristian alternatives to generosity; they are modern expressions of biblical wisdom. They allow people to remain generous without collapsing under cognitive and financial overload. They preserve mental space, and mental space is necessary for discernment, compassion, and faithfulness.

Trusting God’s provision does not require abandoning wisdom. Scripture consistently links generosity with prudence, planning, and stewardship. A constantly overwhelmed mind struggles not only to plan economically but also to love well.

Reducing cognitive overload, therefore, is not selfish: it is responsible. It allows individuals to think clearly, strengthen their households, and ultimately increase their capacity to support others meaningfully.

The Oxford study leaves us with a lesson that resonates deeply with both economics and faith. Intelligence is not scarce in Africa; mental bandwidth is. That bandwidth is depleted not only by poverty itself, but by poorly timed obligations, stacked pressures, and repeated shocks without buffers.

If we want stronger families, wiser decisions, and more resilient communities, we must pay attention not only to income, but also to how expectations and responsibilities are structured. Progress will not come only from earning more, but from fewer emergencies, clearer boundaries, and stronger communal systems.

Poverty, it turns out, is not just about how little we have. It is also about how much of our mind it takes away, and how wisely we steward what remains.

 

When AI Gets It Wrong and Why That Shouldn’t Scare Us

By

Richard Sebaggala (PhD)

Stories about lawyers being “caught using AI wrongly” have become a familiar feature of professional headlines. One recent case in Australia illustrates the pattern. A King’s Counsel, together with junior counsel and their instructing solicitor, was referred to state disciplinary bodies after artificial intelligence–generated errors were discovered in court submissions. The documents contained fabricated or inaccurate legal references—so-called hallucinations—which were not identified before filing. When the court sought an explanation, the responses were unsatisfactory. Costs were awarded against the legal team, and responsibility for the errors became a matter for regulators.

The episode was widely reported, often with a tone of alarm. Artificial intelligence, the implication ran, had intruded into the courtroom with damaging consequences. The lesson appeared obvious: AI is unreliable and should be kept well away from serious professional work.

That conclusion, however, is too simple—and ultimately unhelpful. The problem in this case was not that artificial intelligence produced errors. It was that its output was treated as authoritative rather than provisional. What failed was not the technology itself, but the assumptions made about what the technology could do.

Hallucinations are not moral lapses, nor are they merely the result of careless users. They are a structural limitation of current large language models, arising from how these systems are built and trained. Even developers acknowledge that hallucinations have not been fully eliminated. To frame such incidents as scandals is to overlook a more productive question: how should AI be used, and where should it not be trusted?

A small experiment of my own makes the point more clearly. I recently asked ChatGPT to convert students’ group course marks into an Excel-style table, largely to avoid the tedium of manual data entry. The task involved nothing more than copying names, registration numbers, and marks into a clean, structured format. The result looked impeccable at first glance—neatly aligned, professionally presented, and entirely plausible. Yet closer inspection revealed several errors. Registration numbers had been swapped between students, and in some cases, marks were attributed to the wrong individuals, despite the original data being correct.

When I queried why such mistakes had occurred, given the simplicity of the task, the answer lay in how AI systems operate. These models do not “see” data as humans do. They do not inherently track identity, ownership, or factual relationships unless those constraints are explicitly imposed. Instead, they generate text by predicting what is most likely to come next, based on patterns absorbed during training.

When faced with structured material—tables, grades, legal citations, or names linked to numbers—the system tends to prioritise surface coherence over factual precision. The output looks right, but there is no internal mechanism verifying consistency or truth. This is the same dynamic that produced fabricated case citations in the King’s Counsel matter, and it is why hallucinations also appear in academic references, medical summaries, and financial reports.

Language models are not databases, nor are they calculators. They generate language probabilistically. When asked to reproduce or reorganise factual information, they may quietly reshape it, smoothing entries or rearranging details in ways that make linguistic sense but undermine accuracy. The problem is compounded by the absence of an internal truth-checking function. Unless an AI system is deliberately connected to verified external sources—databases, spreadsheets, citation tools—it has no reliable way of knowing when it is wrong. Confidence, in this context, is meaningless.

The risk increases further when many similar elements appear together. Names, numbers, and references can blur, particularly in long or complex prompts. That is what happened in my grading exercise and what appears to have happened in the legal case. Add to this the way such systems are trained—rewarded for producing answers rather than declining to respond—and the persistence of hallucinations becomes easier to understand. Faced with uncertainty, the model will usually generate something rather than admit ignorance.

This is why the lawyers involved did not err simply by using AI. They erred by relying on its output without independent verification. The same risk confronts lecturers, accountants, doctors, policy analysts, and researchers. In all these fields, responsibility does not shift to the machine. It remains with the professional.

Used properly, artificial intelligence is a powerful tool. It excels at drafting, organising ideas, summarising material, and reducing the burden of repetitive work. It can free time for deeper thinking and better judgment. Where it remains weak is in factual custody, precise attribution, and tasks where small errors carry serious consequences. Confusing these roles is what turns a useful assistant into a liability.

The lesson to draw from recent headlines is therefore not that AI should be avoided. It is that its limits must be understood. AI can work alongside human judgment, but it cannot replace it. When that boundary is respected, the technology becomes a collaborator rather than a shortcut—an amplifier of human reasoning rather than a substitute for it.

Fear, in this context, is the wrong response. What is needed instead is literacy: a clear-eyed understanding of what AI can do well, what it does poorly, and where human oversight is indispensable. The gains on offer—in productivity, creativity, and learning—are too substantial to be dismissed on the basis of misunderstood failures.

 

Marriage Isn’t Dying in Africa—It’s Being Constrained

By Richard Sebaggala (PhD)

 

Today, while preparing to publish my weekly article on the economics of artificial intelligence, I came across an article titled “What’s Killing Marriage—Unmarriageable Men or Liberal Women?” by Maria Baer and Brad Wilcox. The article draws on new US survey evidence showing a sharp decline in women’s confidence in marriage. According to recent Pew data, the share of 12th-grade girls in the United States who say they expect to get married one day has fallen from 83 percent in 1993 to 61 percent in 2023—a drop of more than twenty percentage points in just three decades. Over the same period, young men’s desire for marriage has remained relatively stable at around 75 percent.

 

These figures are striking. They suggest that marriage in the United States is increasingly being questioned not because men have abandoned it, but because many women no longer believe it will improve their lives. Among liberal women in particular, marriage and childbearing now rank low compared to priorities such as career fulfillment, financial security, and emotional well-being. This shift has generated intense debate in the West about whether the decline of marriage reflects male economic decline, feminist ideology, cultural change, or the corrosive influence of digital technology.

 

Reading this, I found myself asking a different question. If marriage is described as “alarming” in a high-income country like the United States, with relatively strong institutions and social safety nets, what does the marriage story look like in Africa?

 

After stepping back and considering both data and lived realities across African societies, it becomes clear that Africa is not experiencing the same phenomenon. The weakening of marriage in Africa does not stem from a loss of faith in the institution itself. In fact, most African women still express strong aspirations for marriage and family life. Marriage remains central to social identity, respectability, and life meaning across cultures, religions, and income groups. Yet marriage is increasingly delayed, informal, or avoided in practice. This apparent contradiction points to a different underlying problem.

 

What Africa is facing is not ideological rejection, but what can best be described as aspirational frustration. Many women want marriage, but they do not want poor-quality marriages. Expectations around economic stability, emotional maturity, mutual respect, and security have risen, while the conditions necessary to meet those expectations have deteriorated. As a result, marriage is postponed, approached cautiously, or entered into only under strict conditions. It is not rejected in principle, but deferred in practice.

 

A central driver of this frustration lies in the political economy of male economic vulnerability. Much like in the United States, African public discourse often speaks of a shortage of “marriageable men.” But in Africa, this is less a story of cultural malaise and more one of structural exclusion. High youth unemployment, widespread informality, unstable incomes, and delayed economic independence make it difficult for many men to meet longstanding expectations of provision and responsibility. Since marriage in many African societies remains closely tied to economic readiness, this instability increases the risks associated with formal unions, especially for women who disproportionately bear the long-term costs of household failure and childrearing.

 

Digital technology is also reshaping expectations, though in a different way from the West. Rather than fueling explicit ideological opposition to marriage, social media in Africa rapidly globalizes lifestyles, aspirations, and relationship ideals. Exposure to highly curated images of success, romance, and consumption raises expectations faster than incomes grow and institutions adapt. Traditional responsibilities remain in place, modern aspirations multiply, and economic capacity lags behind both. The result is growing dissatisfaction not with marriage itself, but with the likelihood of achieving a version of marriage that feels stable and dignified.

 

Importantly, marriage in Africa still correlates strongly with well-being when it works. Evidence from household surveys and well-being studies consistently shows higher life satisfaction among those in stable unions, especially where economic stress and conflict are limited. However, as marital quality deteriorates under economic and social strain, the benefits of marriage weaken. For many women, delaying marriage becomes a rational strategy to avoid long-term vulnerability rather than a rejection of family life.

 

This means that marriage in Africa is not dying; it is being constrained. It is gradually shifting from an expected life stage to a high-stakes decision, from a collective institution to an individual risk calculation. If current trends continue without meaningful economic and institutional reform, the likely outcomes are continued delays in formal marriage, growth of informal and unstable unions, and increasing single parenthood driven not by ideology, but by constrained choices.

 

The contrast with the United States is therefore crucial. While many women in the US are losing faith in marriage as an institution—clearly reflected in the sharp decline in stated desire to marry—many women in Africa still believe in marriage but cannot find the conditions that make it viable. Africa’s marriage challenge is not primarily about values or belief. It is about economics, employment, and the widening gap between aspirations and lived realities.

 

Conditions, unlike beliefs, can be changed. But doing so requires moving beyond moral panic and imported culture wars, and instead treating marriage as part of Africa’s broader social and economic infrastructure. If we are willing to confront the structural roots of aspirational frustration, marriage in Africa remains a resilient institution—not because people are clinging to it blindly, but because they are still waiting for it to work.